Traffic network sensor placement

• US 9,466,209 B2
• Filed: 01/09/2015
• Issued: 10/11/2016
• Est. Priority Date: 01/09/2015
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Blandin, Sebastien, Jabari, Saif Eddin, Wynter, Laura
• Primary Examiner(s): Edwards, Jerrah
• Assistant Examiner(s): WEBER, TAMARA L
• Application Number:
  US14/592,948
• Publication Number:
  US 20160203712A1
• Time in Patent Office: 641 Days
• US Class Current: 1/1
• CPC Class Codes: G08G 1/0116 from roadside infrastructure, e.g. beacons
• CPC Class Codes: G08G 1/0125 Traffic data processing
• CPC Class Codes: G08G 1/0129 for creating historical data or processing based on historical data
• CPC Class Codes: G08G 1/0133 for classifying traffic situation
• CPC Class Codes: G08G 1/0141 for traffic information dissemination
• CPC Class Codes: G08G 1/052 with provision for determining speed or overspeed speed measuring in general G01P

Abstract

Locations for traffic sensors can be determined by a computer system that identifies a particular segment of a travel path. Traffic flow data from other segments of travel path are accessed based on traffic flow characteristics of the particular path. Using the traffic flow data, parameters for a traffic incident symptom propagation model are generated, and a location of a traffic incident along the segment of the path is determined. Using time-to-detection limits and the incident model, upstream and downstream distances are determined, and the locations of two sensors are identified based on the distances.

Claims

1. A computer implemented method comprising:

identifying a particular segment of a travel path that has traffic flow characteristics;

accessing, based upon the traffic flow characteristics, traffic flow data for segments of a set of travel paths, the traffic flow data collected from sensors along the set of travel paths;

generating, based on the accessed traffic flow data, parameters for a traffic incident symptom propagation model;

determining, based upon the traffic incident symptom propagation model for the particular segment, a traffic incident location along the particular segment of the travel path wherein the determining the traffic incident location comprises determining, based on incident symptom propagation speed functions for an upstream symptom and a downstream symptom, a traffic incident location relative to an incident symptom propagation speed function for an upstream and downstream symptom;

determining, based on a first time-to-detection limit and using the traffic incident symptom propagation model, an upstream distance;

determining, based on the first time-to-detection limit and using the model, a downstream distance;

outputting, based upon the upstream and downstream distances, a sensor location on the particular segment of the travel path for a first sensor and a second sensor;

transmitting the first sensor location at a first end of the particular segment of the travel path and the second sensor location at a second end of the particular segment of the travel path; and

displaying, on a display, the first sensor location and the second sensor location.

2. The method of claim 1, wherein the traffic flow characteristics comprise a traffic density threshold;

and

wherein the method further comprises generating the traffic incident symptom propagation model using the traffic density threshold.

3. The method of claim 1, wherein the method further comprises determining a location for a third sensor on the travel path, based on another traffic incident symptom propagation model, for another particular segment of the travel path between the second and third sensors.

4. The method of claim 3, wherein the determining the location for the third sensor comprises:

identifying the another particular segment of the travel path between the second and third sensors;

determining, based on another time-to-detection limit, an upstream distance between the second and third sensors;

determining, based on the another time-to-detection limit, a downstream sensor downstream distance between the second and third sensors; and

outputting, based upon the upstream distance and the downstream distance between the second and third sensors, the third sensor location at an end of the another particular segment of the travel path.

5. The method of claim 1, wherein the particular segment of the travel path comprises a roadway with no new traffic entering or exiting the roadway over the particular segment of the travel path.

6. A computer system comprising:

at least one processor circuit having;

a path identifier module configured to;

identify a particular segment of a travel path that has traffic flow characteristics; and

access, based upon the traffic flow characteristics, traffic flow data for segments of a set of travel paths, the traffic flow data collected from sensors along the set of travel paths;

a developer module configured to;

generate, based on the accessed traffic flow data, parameters for a traffic incident symptom propagation model; and

determine, based upon the traffic incident symptom propagation model for the particular segment, a traffic incident location along the particular segment of the travel path, wherein the determining the traffic incident location comprises determining, based on incident symptom propagation speed functions for an upstream symptom and a downstream symptom, a traffic incident location relative to an incident symptom propagation speed function for an upstream and downstream symptom;

a distance determining module configured to;

determine, based on a specified time-to-detection limit and using the model, an upstream distance; and

determine, based on the specified time-to-detection limit and using the model, a downstream distance; and

a report module configured to;

output, based upon the upstream and downstream distances, a sensor location on the particular segment of the travel path for a first sensor and a second sensor;

transmit the first sensor location at a first end of the particular segment of the travel path and the second sensor location at a second end of the particular segment of the travel path; and

display, on a display, the first sensor location and the second sensor location.

7. The system of claim 6, wherein the traffic flow characteristics comprise a traffic density threshold;

and

wherein the developer module is further configured to generate the traffic incident symptom propagation model using the traffic density threshold.

8. The system of claim 6, wherein the at least one processor circuit is configured to determine a location for a third sensor on the travel path, based on another traffic incident symptom propagation model, for another particular segment of the travel path between the second and third sensors.

9. The system of claim 8, wherein the at least one processor circuit is configured to determine the location for the third sensor by:

identifying the another particular segment of the travel path between the second and third sensors;

determining, based on another time-to-detection limit, an upstream distance between the second and third sensors;

determining, based on the another time-to-detection limit, a downstream sensor downstream distance between the second and third sensors; and

outputting, based upon the upstream and downstream distance between the second and third sensors, the third sensor location at an end of the another particular segment of the travel path.

10. The system of claim 6, wherein the particular segment of the travel path comprises a roadway with no new traffic entering or exiting the roadway over the particular segment of the travel path.

11. A computer program product comprising a computer readable storage medium having program instructions embodied therewith, wherein the computer readable storage medium is not a transitory signal per se, the program instructions executable by a computer processing circuit to cause the circuit to perform the method comprising:

identifying a particular segment of a travel path that has traffic flow characteristics;

accessing, based upon the traffic flow characteristics, traffic flow data for segments of a set of travel paths, the traffic flow data collected from sensors along the set of travel paths;

generating, based on the accessed traffic flow data, parameters for a traffic incident symptom propagation model;

determining, based upon the traffic incident symptom propagation model for the particular segment, a traffic incident location along the particular segment of the travel path, wherein the determining the traffic incident location comprises determining, based on incident symptom propagation speed functions for an upstream symptom and a downstream symptom, a traffic incident location relative to an incident symptom propagation speed function for an upstream and downstream symptom;

determining, based on a first time-to-detection limit and using the traffic incident symptom propagation model, an upstream distance;

determining, based on the first time-to-detection limit and using the model, a downstream distance;

outputting, based upon the upstream and downstream distances, a sensor location on the particular segment of the travel path for a first sensor and a second sensor;

transmitting the first sensor location at a first end of the particular segment of the travel path and the second sensor location at a second end of the particular segment of the travel path; and

displaying, on a display, the first sensor location and the second sensor location.

12. The computer program product of claim 11, wherein the traffic flow characteristics comprise a traffic density threshold;

and

wherein the method further comprises generating the traffic incident symptom propagation model using the traffic density threshold.

13. The computer program product of claim 11, wherein the method further comprises determining a location for a third sensor on the travel path, based on another traffic incident symptom propagation model, for another particular segment of the travel path between the second and third sensors.

14. The computer program product of claim 13, wherein the determining the location for the third sensor comprises:

identifying the another particular segment of the travel path between the second and third sensors;

determining, based on another time-to-detection limit, an upstream distance between the second and third sensors;

determining, based on the another time-to-detection limit, a downstream sensor downstream distance between the second and third sensors; and

outputting, based upon the upstream distance and the downstream distance between the second and third sensors, the third sensor location at an end of the another particular segment of the travel path.

15. The computer program product of claim 11, wherein the particular segment of the travel path comprises a roadway with no new traffic entering or exiting the roadway over the particular segment of the travel path.